Adapting Large Language Models via Reading Comprehension
OpenBA: An Open-sourced 15B Bilingual Asymmetric seq2seq Model Pre-trained from Scratch
PDFTriage: Question Answering over Long, Structured Documents
Sorted LLaMA: Unlocking the Potential of Intermediate Layers of Large Language Models for Dynamic Inference Using Sorted Fine-Tuning (SoFT)
An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models
MindAgent: Emergent Gaming Interaction
Struc-Bench: Are Large Language Models Really Good at Generating Complex Structured Data?
Recovering from Privacy-Preserving Masking with Large Language Models
S3-DST: Structured Open-Domain Dialogue Segmentation and State Tracking in the Era of LLMs
Augmenting text for spoken language understanding with Large Language Models
Language Modeling Is Compression
Baichuan 2: Open Large-scale Language Models
Stabilizing RLHF through Advantage Model and Selective Rehearsal
Chain-of-Verification Reduces Hallucination in Large Language Models
LMDX: Language Model-based Document Information Extraction and Localization
SlimPajama-DC: Understanding Data Combinations for LLM Training
Contrastive Decoding Improves Reasoning in Large Language Models
CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages
A Data Source for Reasoning Embodied Agents
Leveraging Contextual Information for Effective Entity Salience Detection
LASER: LLM Agent with State-Space Exploration for Web Navigation
Sparse Autoencoders Find Highly Interpretable Features in Language Models
Investigating Answerability of LLMs for Long-Form Question Answering
Scaling Laws for Sparsely-Connected Foundation Models
Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers
Ambiguity-Aware In-Context Learning with Large Language Models
Are Large Language Model-based Evaluators the Solution to Scaling Up Multilingual Evaluation?
Clinical Text Summarization: Adapting Large Language Models Can Outperform Human Experts
Agents: An Open-source Framework for Autonomous Language Agents
Statistical Rejection Sampling Improves Preference Optimization
Large Language Models for Compiler Optimization
AstroLLaMA: Towards Specialized Foundation Models in Astronomy
Large Language Model for Science: A Study on P vs. NP
Efficient Memory Management for Large Language Model Serving with PagedAttention
FIAT: Fusing learning paradigms with Instruction-Accelerated Tuning
Optimize Weight Rounding via Signed Gradient Descent for the Quantization of LLMs
When Less is More: Investigating Data Pruning for Pretraining LLMs at Scale
Neurons in Large Language Models: Dead, N-gram, Positional
Textbooks Are All You Need II: phi-1.5 technical report
DrugChat: Towards Enabling ChatGPT-Like Capabilities on Drug Molecule Graphs
From Sparse to Dense: GPT-4 Summarization with Chain of Density Prompting
XGen-7B Technical Report
DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models
GPT Can Solve Mathematical Problems Without a Calculator
Large Language Models as Optimizers
Efficient RLHF: Reducing the Memory Usage of PPO
ModelScope-Agent: Building Your Customizable Agent System with Open-source Large Language Models
Open Problems and Fundamental Limitations of Reinforcement Learning from Human Feedback [Summary]
Llama 2: Open Foundation and Fine-Tuned Chat Models [Commentary]
Challenges and Applications of Large Language Models [Summary]
LoraHub: Efficient Cross-Task Generalization Via Dynamic LoRA Composition [Commentary]
ToolLLM: Facilitating Large Language Models To Master 16000+ Real-World APIs [Commentary]
FacTool: Factuality Detection in Generative AI -- A Tool Augmented Framework for Multi-Task and Multi-Domain Scenarios
Graph of Thoughts: Solving Elaborate Problems with Large Language Models
Efficient Guided Generation for Large Language Models
Predicting transcriptional outcomes of novel multigene perturbations with GEARS
A Survey on Model Compression for Large Language Models
From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Models
LLM As DBA
Self-Alignment with Instruction Backtranslation
RLAIF: Scaling Reinforcement Learning from Human Feedback with AI Feedback
Large Content And Behavior Models To Understand, Simulate, And Optimize Content And Behavior
BioCoder: A Benchmark for Bioinformatics Code Generation with Contextual Pragmatic Knowledge
The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants
Can Programming Languages Boost Each Other via Instruction Tuning?
WeatherBench 2: A benchmark for the next generation of data-driven global weather models
Jais and Jais-chat: Arabic-Centric Foundation and Instruction-Tuned Open Generative Large Language Models
MedAlign: A Clinician-Generated Dataset for Instruction Following with Electronic Medical Records
SoTaNa: The Open-Source Software Development Assistant
Teach LLMs to Personalize -- An Approach inspired by Writing Education
RAVEN: In-Context Learning with Retrieval Augmented Encoder-Decoder Language Models
Solving Challenging Math Word Problems Using GPT-4 Code Interpreter with Code-based Self-Verification
The Devil is in the Errors: Leveraging Large Language Models for Fine-grained Machine Translation Evaluation
CausalLM is not optimal for in-context learning
Platypus: Quick, Cheap, and Powerful Refinement of LLMs
OctoPack: Instruction Tuning Code Large Language Models
Enhancing Network Management Using Code Generated by Large Language Models
Improving Joint Speech-Text Representations Without Alignment
BOLAA: Benchmarking and Orchestrating LLM-augmented Autonomous Agents
PIPPA: A Partially Synthetic Conversational Dataset
Self-Alignment with Instruction Backtranslation
OpenProteinSet: Training data for structural biology at scale
Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment
Accelerating LLM Inference with Staged Speculative Decoding
Shepherd: A Critic for Language Model Generation
SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore
Simple synthetic data reduces sycophancy in large language models
Cure the headache of Transformers via Collinear Constrained Attention
Sparse Autoencoders Find Highly Interpretable Features in Language Models
Scaling Laws for Sparsely-Connected Foundation Models
Uncovering mesa-optimization algorithms in Transformers
Gated recurrent neural networks discover attention
One Wide Feedforward is All You Need
Vector Search with OpenAI Embeddings: Lucene Is All You Need
Bayesian Flow Networks
YaRN: Efficient Context Window Extension of Large Language Models
LM-Infinite: Simple On-the-Fly Length Generalization for Large Language Models
Composable Function-preserving Expansions for Transformer Architectures
Sparse Autoencoders Find Highly Interpretable Features in Language Models